With the recent successes in using deep
learning techniques to solve computer vision problems, the performances of the
state of the art algorithms in many areas, especially object recognition, have
been dramatically improved. Researchers are now inspired to address yet more
challenging problems, such as associating pictures with aesthetics, and have
also reported progress. One remaining final frontier in extracting meaning from
images is related to the recognition of emotions that images arouse in humans.
The key challenges are the loose and highly abstract nature of semantics
associated with emotions. We will discuss how to effectively employ a
data-intensive approach to emotion recognition in images, as well as multimedia
that include both image and text information.

Bio:

Professor Jiebo Luo joined the University
of Rochester (UR) in 2011 after a prolific career of over fifteen years at
Kodak Research Laboratories. He has been involved in numerous technical
conferences, including serving as the program co-chair of ACM Multimedia 2010, IEEE
CVPR 2012, and IEEE ICIP 2017. He has served as the Editor-in-Chief of the
Journal of Multimedia, and on the editorial boards of the IEEE Transactions on Pattern Analysis and Machine
Intelligence (TPAMI), IEEE Transactions on Multimedia (TMM), IEEE Transactions
on Circuits and Systems for Video Technology (TCSVT), Pattern Recognition, Machine Vision and
Applications, and Journal of Electronic Imaging. He is a Fellow of the SPIE, IEEE, and IAPR. He is a
Data Science Distinguished Researcher with the CoE Goergen Institute for Data Science (IDS) at
UR.